ADOPSI FITUR FACE RECOGNITION PADA APLIKASI FOTOYU: ANALISIS DENGAN MODEL UTAUT MODIFIKASI
DOI:
https://doi.org/10.32699/biner.v5i2.11998Keywords:
Face Recognition, FotoYu, UTAUT, IPMA, SEM-PLSAbstract
Penelitian ini mengeksplorasi faktor yang memengaruhi niat penggunaan fitur pengenalan wajah pada aplikasi FotoYu dengan responden 17 tahun dan menggunakan model UTAUT modifikasi. Data dari 473 responden yang didapatkan dianalisis menggunakan Partial Least Squares Structural Equation Modelling (PLS-SEM) dan Importance-Performance Map Analysis (IPMA). Hasil PLS-SEM menunjukkan Performance Expectancy ( = 0.328, < 0.001), Personal Innovativeness ( = 0.349, < 0.001), dan Trust in The System ( = 0.171, < 0.001) berpengaruh positif signifikan terhadap Acceptance Intention, serta berada di Kuadran I (Keep Up The Good Work) pada IPMA. Sebaliknya, Privacy Risk ( = -0,354, <0,001) dan Performance Risk ( = -0.533, <0.001) berpengaruh negatif signifikan terhadap Trust in The System. Pengujian hipotesis secara statistik membuktikan bahwa Trust in The System secara signifikan memediasi pengaruh negatif Privacy Risk (indirect effect, = -0.060, 0.001) dan Performance Risk (indirect effect, = -0.091, 0.001) terhadap niat adopsi. Melalui mediasi ini, Trust in The System menjadi variabel kunci di Kuadran I dengan nilai Importance sebesar 0.171 dan Performance 61.229 yang berada di atas rata-rata ambang batas. Hal ini menegaskan pentingnya kepercayaan dan inovasi pribadi, di mana Personal Innovativeness menjadi pendorong adopsi terbesar dalam implementasi fitur pengenalan wajah secara efektif.
Downloads
References
[1] Supergiga, ‘Fotoyu’, https://www.fotoyu.com/how-it-works.
[2] PT Super Giga Generasi, ‘Fotoyu’. Accessed: Oct. 23, 2025. [Online]. Available: https://play.google.com/store/apps/details?id=com.supergiga.generasi&hl=id
[3] ‘UU Nomor 27 Tahun 2022’, Oct. 2022. Accessed: Jul. 06, 2026. [Online]. Available: https://peraturan.bpk.go.id/Details/229798/uu-no-27-tahun-2022
[4] S. Sternad Zabukovšek, S. Bobek, U. Zabukovšek, Z. Kalinić, and P. Tominc, ‘Enhancing PLS-SEM-Enabled Research with ANN and IPMA: Research Study of Enterprise Resource Planning (ERP) Systems’ Acceptance Based on the Technology Acceptance Model (TAM)’, Mathematics, vol. 10, no. 9, p. 1379, Apr. 2022, doi: 10.3390/math10091379.
[5] M. Syafri, A. Prawira Buana, and R. Rustan, ‘Diburu Lensa, Dilindungi Hukum: Urgensi Perlindungan Hukum atas Potret Tak Berizin di Era Aplikasi FOTOYU’, Legal Dialogica, vol. 1, no. 1, pp. 1–10, Sep. 2025.
[6] N. Ulya Qinvi, R. Sa’dillah Ahmad, and H. Wahyunisa, ‘Perlindungan Data Pribadi dalam Marketplace Foto Berbasis Kecerdasan Buatan pada Platform FotoYu’, 2026. [Online]. Available: https://www.fotoyu.com/how-it-works
[7] H. L. Gururaj, B. C. Soundarya, S. Priya, J. Shreyas, and F. Flammini, ‘A Comprehensive Review of Face Recognition Techniques, Trends, and Challenges’, IEEE Access, vol. 12, pp. 107903–107926, 2024, doi: 10.1109/ACCESS.2024.3424933.
[8] Y. Kortli, M. Jridi, A. Al Falou, and M. Atri, ‘Face Recognition Systems: A Survey’, Sensors, vol. 20, no. 2, p. 342, Jan. 2020, doi: 10.3390/s20020342.
[9] M. Wang, Y. Kang, B. Deng, and X. Lan, ‘Exploring college students’ risk perception and acceptance intention of facial recognition technology in China’, Telematics and Informatics, vol. 95, Nov. 2024, doi: 10.1016/j.tele.2024.102193.
[10] N. Rusliani, W. R. Hidayani, and H. Sulistyoningsih, ‘Literature Review: Faktor-Faktor yang Berhubungan dengan Kejadian Stunting pada Balita’, Buletin Ilmu Kebidanan dan Keperawatan, vol. 1, no. 01, pp. 32–40, Aug. 2022, doi: 10.56741/bikk.v1i01.39.
[11] S. Byun and S.-E. Byun, ‘Exploring perceptions toward biometric technology in service encounters: a comparison of current users and potential adopters’, Behaviour & Information Technology, vol. 32, no. 3, pp. 217–230, Mar. 2013, doi: 10.1080/0144929X.2011.553741.
[12] Venkatesh, Morris, Davis, and Davis, ‘User Acceptance of Information Technology: Toward a Unified View’, MIS Quarterly, vol. 27, no. 3, p. 425, 2003, doi: 10.2307/30036540.
[13] B. Nyesiga Catherine, K. Mayoka Geofrey, M. B. Moya, and G. Aballo, ‘Effort Expectancy, Performance Expectancy, Social Influence and Facilitating Conditions as Predictors of Behavioural Intentions to use ATMS with Fingerprint Authentication in Ugandan Banks’, 2017.
[14] O. Ciftci, E. K. (Cindy) Choi, and K. Berezina, ‘Let’s face it: Are customers ready for facial recognition technology at quick-service restaurants?’, Int. J. Hosp. Manag., vol. 95, May 2021, doi: 10.1016/j.ijhm.2021.102941.
[15] M. Deutsch, ‘The Effect of Motivational Orientation upon Trust and Suspicion’, Human Relations, vol. 13, no. 2, pp. 123–139, May 1960, doi: 10.1177/001872676001300202.
[16] N. Lankton, D. H. McKnight, and J. Tripp, ‘Technology, Humanness, and Trust: Rethinking Trust in Technology’, J. Assoc. Inf. Syst., vol. 16, no. 10, pp. 880–918, Oct. 2015, doi: 10.17705/1jais.00411.
[17] E. Moriuchi and I. Takahashi, ‘Satisfaction Trust and Loyalty of Repeat Online Consumer within the Japanese Online Supermarket Trade’, Australasian Marketing Journal, vol. 24, no. 2, pp. 146–156, May 2016, doi: 10.1016/j.ausmj.2016.02.006.
[18] E. Moriuchi, ‘Okay, Google!: An empirical study on voice assistants on consumer engagement and loyalty’, Psychol. Mark., vol. 36, no. 5, pp. 489–501, May 2019, doi: 10.1002/mar.21192.
[19] B. Hu, Y. Liu, and W. Yan, ‘Should I scan my face? The influence of perceived value and trust on Chinese users’ intention to use facial recognition payment’, Telematics and Informatics, vol. 78, p. 101951, Mar. 2023, doi: 10.1016/j.tele.2023.101951.
[20] C. Li and H. Li, ‘Disentangling facial recognition payment service usage behavior: A trust perspective’, Telematics and Informatics, vol. 77, Feb. 2023, doi: 10.1016/j.tele.2023.101939.
[21] Ngugi, Kamis, and Tremaine, ‘Intention to Use Biometric Systems’, e-Service Journal, vol. 7, no. 3, p. 20, 2011, doi: 10.2979/eservicej.7.3.20.
[22] C.-K. Pai, T.-W. Wang, S.-H. Chen, and K.-Y. Cai, ‘Empirical study on Chinese tourists’ perceived trust and intention to use biometric technology’, Asia Pacific Journal of Tourism Research, vol. 23, no. 9, pp. 880–895, Sep. 2018, doi: 10.1080/10941665.2018.1499544.
[23] C. Phonthanukitithaworn, C. Sellitto, and M. Fong, ‘Journal of Internet Banking and Commerce User Intentions to Adopt Mobile Payment Services: A Study of Early Adopters in Thailand’, 2015. [Online]. Available: http://www.arraydev.com/commerce/jibc/
[24] R. N. Stone and K. Grønhaug, ‘Perceived Risk: Further Considerations for the Marketing Discipline’, Eur. J. Mark., vol. 27, no. 3, pp. 39–50, Apr. 1993, doi: 10.1108/03090569310026637.
[25] A. M. Hassan, M. B. Kunz, and A. W. Pearson, ‘CONCEPTUALIZATION AND MEASUREMENT OF PERCEIVED RISK IN ONLINE SHOPPING’, Marketing Management Journal, vol. 16, no. 1, p. 136, 2006.
[26] S. Yousafzai, J. Pallister, and G. Foxall, ‘Multi-dimensional role of trust in Internet banking adoption’, The Service Industries Journal, vol. 29, no. 5, pp. 591–605, May 2009, doi: 10.1080/02642060902719958.
[27] T. L. Shofa and N. Komariyatin, ‘Pengaruh Customer Trust dan Perceived Risk terhadap Purchase Decision pada Produk Skintific dengan Customer Satisfaction sebagai Variabel Mediasi’, SENTRI: Jurnal Riset Ilmiah, vol. 5, no. 2, pp. 1822–1837, Feb. 2026, doi: 10.55681/sentri.v5i2.5759.
[28] E. M. . Rogers, Diffusion of innovations. Free Press, 1995.
[29] R. Agarwal and J. Prasad, ‘A Conceptual and Operational Definition of Personal Innovativeness in the Domain of Information Technology’, Information Systems Research, vol. 9, no. 2, pp. 204–215, Jun. 1998, doi: 10.1287/isre.9.2.204.
[30] S. K. Ahmed, ‘How to choose a sampling technique and determine sample size for research: A simplified guide for researchers’, Oral Oncology Reports, vol. 12, p. 100662, Dec. 2024, doi: 10.1016/j.oor.2024.100662.
[31] A. Zrineh, M. Al‐Usta, and A. Alwawi, ‘Sampling Methods and Sample Size Determination in Clinical Research: An Educational Review’, J. Gen. Fam. Med., vol. 27, no. 1, Jan. 2026, doi: 10.1002/jgf2.70096.
[32] A. M. Sharifnia, D. E. Kpormegbey, D. K. Thapa, and M. Cleary, ‘A Primer of Data Cleaning in Quantitative Research: Handling Missing Values and Outliers’, J. Adv. Nurs., vol. 82, no. 1, pp. 970–975, Jan. 2026, doi: 10.1111/jan.16908.
[33] T. Yu, C. Wang, Q. Bian, and A. P. Teoh, ‘Acceptance of or resistance to facial recognition payment: A systematic review’, Journal of Consumer Behaviour, vol. 23, no. 6, pp. 2933–2951, Nov. 2024, doi: 10.1002/cb.2385.
[34] Y. Lin, Y. Huang, and Y. Li, ‘Research on Hotel Guests’ Acceptance of Face Recognition Systems Based on the UTAUT’, Lecture Notes in Education, Arts, Management and Social Science, vol. 3, no. 2, pp. 210–216, Mar. 2025, doi: 10.18063/lne.v3i2.776.
[35] T. Yu and A. P. Teoh, ‘Factors Influencing Consumers’ Behavioral Intention to Use Facial Recognition Payment on E-Commerce Platforms in China’, 2024. [Online]. Available: https://www.wjx.cn/
[36] D. Nan, Y. Kim, J. Huang, H. S. Jung, and J. H. Kim, ‘Factors Affecting Intention of Consumers in Using Face Recognition Payment in Offline Markets: An Acceptance Model for Future Payment Service’, Front. Psychol., vol. 13, Mar. 2022, doi: 10.3389/fpsyg.2022.830152.
[37] Y. Guo and H. N. Waked, ‘Trust-Mediated adoption of AI Robo-Advisors in inland china: an extended UTAUT perspective’, Journal of Financial Services Marketing, vol. 31, no. 1, p. 11, Mar. 2026, doi: 10.1057/s41264-025-00339-2.
[38] L. Chen, J. Jia, and C. Wu, ‘Factors influencing the behavioral intention to use contactless financial services in the banking industry: An application and extension of UTAUT model’, Front. Psychol., vol. 14, Mar. 2023, doi: 10.3389/fpsyg.2023.1096709.
[39] Y. Kim, V. Blazquez, and T. Oh, ‘Determinants of Generative AI System Adoption and Usage Behavior in Korean Companies: Applying the UTAUT Model’, Behavioral Sciences, vol. 14, no. 11, p. 1035, Nov. 2024, doi: 10.3390/bs14111035.
[40] S. Srivastava, A. Mohta, and V. Shunmugasundaram, ‘Adoption of digital payment FinTech service by Gen Y and Gen Z users: evidence from India’, Digital Policy, Regulation and Governance, vol. 26, no. 1, pp. 95–117, Jan. 2024, doi: 10.1108/DPRG-07-2023-0110.
[41] T. Yu, A. P. Teoh, C. Wang, and Q. Bian, ‘Convenient or risky? Investigating the behavioral intention to use facial recognition payment in smart hospitals’, Humanit. Soc. Sci. Commun., vol. 11, no. 1, Dec. 2024, doi: 10.1057/s41599-024-03910-9.
[42] N. Martin and F. M. Metzger, ‘What Determines the Acceptance of Digital Identity and Facial Recognition-Based Technologies? Evidence From an eID System and a Multi-Country Survey’, Journal of Innovation Management, vol. 13, no. 2, pp. 129–173, Nov. 2025, doi: 10.24840/2183-0606_013.002_0006.
[43] M. Liu, C. Wang, and J. Hu, ‘Understanding older adults’ adoption of facial recognition payment: An integrated model of TAM and UXT’, PLoS One, vol. 20, no. 7 July, Jul. 2025, doi: 10.1371/journal.pone.0325291.
[44] Z. Kenesei, L. Kökény, K. Ásványi, and M. Jászberényi, ‘The central role of trust and perceived risk in the acceptance of autonomous vehicles in an integrated UTAUT model’, European Transport Research Review, vol. 17, no. 1, Dec. 2025, doi: 10.1186/s12544-024-00681-x.
[45] K. Tamilmani, N. P. Rana, and Y. K. Dwivedi, ‘Consumer Acceptance and Use of Information Technology: A Meta-Analytic Evaluation of UTAUT2’, Information Systems Frontiers, vol. 23, no. 4, pp. 987–1005, Aug. 2021, doi: 10.1007/s10796-020-10007-6.
[46] G. Kostka, L. Steinacker, and M. Meckel, ‘Between security and convenience: Facial recognition technology in the eyes of citizens in China, Germany, the United Kingdom, and the United States’, Public Understanding of Science, vol. 30, no. 6, pp. 671–690, Aug. 2021, doi: 10.1177/09636625211001555.
[47] M. Andrejevic and N. Selwyn, ‘Facial recognition technology in schools: critical questions and concerns’, Learn. Media Technol., vol. 45, no. 2, pp. 115–128, Apr. 2020, doi: 10.1080/17439884.2020.1686014.
[48] H. T. Lim, A. Vafaei-Zadeh, H. Hanifah, and D. Nikbin, ‘Evaluating the benefits and risks of facial recognition payment systems adoption in Malaysia’, International Journal of Bank Marketing, vol. 43, no. 2, pp. 292–320, Jan. 2025, doi: 10.1108/IJBM-05-2024-0300.
[49] B. Meden et al., ‘Privacy–Enhancing Face Biometrics: A Comprehensive Survey’, IEEE Transactions on Information Forensics and Security, vol. 16, pp. 4147–4183, 2021, doi: 10.1109/TIFS.2021.3096024.
[50] E. Politou, E. Alepis, and C. Patsakis, ‘Forgetting personal data and revoking consent under the GDPR: Challenges and proposed solutions’, J. Cybersecur., vol. 4, no. 1, Jan. 2018, doi: 10.1093/cybsec/tyy001.
[51] S. Garg, S. Goldwasser, and P. N. Vasudevan, ‘Formalizing Data Deletion in the Context of the Right to Be Forgotten’, 2020, pp. 373–402. doi: 10.1007/978-3-030-45724-2_13.
[52] I. G. A. N. C. Pramitha and M. H. , Dr. I. N. B. S.H., ‘Environmental Criminal Action on Forest and Land Burning in Pontianak City’, International Journal of Judicial Law, vol. 4, no. 4, pp. 86–91, 2025, doi: 10.54660/IJJL.2025.4.4.86-91.
[53] D. Dwi Wijayanto, K. Wiwik Indrayanti, and D. A. Wisnu W, ‘Personal Data Protection in Digital Business Based on the Law on Personal Data Protection’, International Journal of Research in Social Science and Humanities, vol. 06, no. 08, pp. 06–12, 2025, doi: 10.47505/IJRSS.2025.8.2.
[54] F. Razi, H. Tuasikal, and D. Pratiwi Markus, ‘Implementation and Challenges of the Personal Data Protection Law in Indonesia’, Jurnal Indonesia Sosial Teknologi, vol. 5, no. 12, pp. 6015–6021, Dec. 2024, doi: 10.59141/jist.v5i12.1285.
[55] Dr. A. Rahman, ‘Safeguarding Privacy in an Interconnected World: Indonesia’s Personal Data Protection Law’, International Journal of Social Sciences, Language and Linguistics, vol. 05, no. 03, pp. 14–18, Mar. 2025, doi: 10.55640/ijssll-05-03-03.
[56] B. L. Nuzul Sa’adah, S. Sukarmi, and R. Dewantara, ‘Establishing A Personal Data Protection Agency for E-Commerce in Indonesia’, Invest Journal of Sharia & Economic Law, vol. 4, no. 2, pp. 292–316, Dec. 2024, doi: 10.21154/invest.v4i2.10031.
[57] W. Gao, N. Jiang, and Q. Guo, ‘Facial recognition payment is cool: coolness, inspiration, and customer continuance intention to use facial recognition payment’, Financial Innovation, vol. 11, no. 1, Dec. 2025, doi: 10.1186/s40854-024-00697-1.
[58] B. Zhang, H. M. Peterson, and W. Sun, ‘PERCEPTION OF DIGITAL SURVEILLANCE: A COMPARATIVE STUDY OF HIGH SCHOOL STUDENTS IN THE U.S. AND CHINA’, Issues In Information Systems, 2017, doi: 10.48009/1_iis_2017_98-108.
[59] S. Anderson, J. Anderson, and C. A. Nguyen, ‘The value of visible work: Operational transparency in digital healthcare interfaces’, Health Mark. Q., vol. 42, no. 4, pp. 353–368, Oct. 2025, doi: 10.1080/07359683.2025.2564584.
[60] M. A. S. Palash, M. S. Talukder, A. K. M. N. Islam, and Y. Bao, ‘Positive and negative valences, personal innovativeness and intention to use facial recognition for payments’, Industrial Management and Data Systems, vol. 122, no. 4, pp. 1081–1108, Apr. 2022, doi: 10.1108/IMDS-04-2021-0230.
[61] Y. Zhong, S. Oh, and H. C. Moon, ‘Service transformation under industry 4.0: Investigating acceptance of facial recognition payment through an extended technology acceptance model’, Technol. Soc., vol. 64, Feb. 2021, doi: 10.1016/j.techsoc.2020.101515.
[62] P. Sharma*, S. Mallick, and A. Srivastava, ‘Understanding Facial Recognition System Usage and Adaptation among Millennial and Non-millennial consumers’, International Journal of Recent Technology and Engineering (IJRTE), vol. 8, no. 4, pp. 12779–12791, Nov. 2019, doi: 10.35940/ijrte.D6066.118419.
[63] D. Hao, S. Samuel, J. T. Purba, and E. Hulu, ‘Key Drivers of Consumers’ Continuance Intention to Use Facial Recognition Payments’, Journal of System and Management Sciences, vol. 14, no. 6, May 2024, doi: 10.33168/JSMS.2024.0625.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Biner : Jurnal Ilmiah Informatika dan Komputer
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
An author who publishes in this Journal agrees to the following terms:
- Author retains the copyright and grants the journal the right of first publication of the work simultaneously licensed under the Creative Commons Attribution-ShareAlike 4.0 License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal
- Author is able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book) with the acknowledgement of its initial publication in this journal.
- Author is permitted and encouraged to post his/her work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of the published work (See The Effect of Open Access).
